Kaggle_Titanic-MachineLearning_from_Disaster.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Titanic: Machine Learning from Disaster\n",
    "Link: https://www.kaggle.com/c/titanic\n",
    "We will try to predict a classification- survival or deceased. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv('dataset/kaggle-titanic/titanic_train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis\n",
    "\n",
    "Let's begin some exploratory data analysis! We'll start by checking out missing data!\n",
    "\n",
    "## Missing Data\n",
    "\n",
    "We can use seaborn to create a simple heatmap to see where we are missing data!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a20978a58>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1847x1800 with 110 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(train, hue='Survived')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10ad2b160>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.isnull()\n",
    "sns.heatmap(train.isnull(),yticklabels=False,cbar=False,cmap='Blues')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like we are just missing too much of that data to do something useful with at a basic level. We'll probably drop this later, or change it to another feature like \"Cabin Known: 1 or 0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1135fc88>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid')\n",
    "sns.countplot(data=train, x='Survived', palette='YlOrRd')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1cdc3c50>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Esc + y -to convert to code, m-markdown\n",
    "# Esc + add cell a- above, b-below\n",
    "# Opt+Ent to run and add cell\n",
    "sns.countplot(data=train, x='Survived', hue='Sex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1ce8fcc0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=train, x='Survived', hue='Pclass')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a1c9b7048>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 426.125x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Linear Regression Model Plot. How total bill affects Bill. \n",
    "#Hue will do multiple regression lines in same graph as per catagories. Column='Smoker' will split graph in 2.\n",
    "#sns.lmplot(data=train, x='TotalBill', y='Bill', hue='IsSmoker') \n",
    "sns.lmplot(data=train, x='Survived', y='Pclass', hue='Sex') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mk194903/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1d0314a8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(train['Age'].dropna(), bins=30) # distribution Plot dropna - drop N/A\n",
    "# or \n",
    "#train['Age'].plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10ad98a20>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train['Fare'].plot.hist(bins=30, figsize=(10,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1d7cd860>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=train, x='Pclass', y='Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def impute_age(cols):\n",
    "    age = cols[0]\n",
    "    pclass = cols[1]\n",
    "    if pd.isnull(age):\n",
    "        if pclass == 1:\n",
    "            return 38\n",
    "        elif pclass == 2:\n",
    "            return 29\n",
    "        else:\n",
    "            return 24\n",
    "    else:\n",
    "        return age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['Age'] = train[['Age', 'Pclass']].apply(impute_age, axis=1) # replace blank age with pClass age mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1d943128>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data=train.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.drop(labels='Cabin', axis=1, inplace=True) # inplace modifies same dataset no need to assign output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sex = pd.get_dummies(train['Sex'], drop_first=True)\n",
    "embark = pd.get_dummies(train['Embarked'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.drop(labels=['Sex','Embarked', 'Name', 'Ticket'], axis=1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.concat([train,sex,embark], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>male</th>\n",
       "      <th>Q</th>\n",
       "      <th>S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass   Age  SibSp  Parch     Fare  male  Q  S\n",
       "0            1         0       3  22.0      1      0   7.2500     1  0  1\n",
       "1            2         1       1  38.0      1      0  71.2833     0  0  0\n",
       "2            3         1       3  26.0      0      0   7.9250     0  0  1\n",
       "3            4         1       1  35.0      1      0  53.1000     0  0  1\n",
       "4            5         0       3  35.0      0      0   8.0500     1  0  1"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data is ready"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PassengerId', 'Survived', 'Pclass', 'Age', 'SibSp', 'Parch', 'Fare',\n",
       "       'male', 'Q', 'S'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Building a Logistic Regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(train.drop('Survived', axis=1), \n",
    "                                                    train['Survived'], \n",
    "                                                    test_size=0.30, random_state=101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#%%time\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "logmodel = LogisticRegression()\n",
    "logmodel.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = logmodel.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.81      0.93      0.87       163\n",
      "          1       0.85      0.66      0.75       104\n",
      "\n",
      "avg / total       0.83      0.82      0.82       267\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[151,  12],\n",
       "       [ 35,  69]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix(y_test, predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Output File for predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test_Out = pd.read_csv('dataset/kaggle-titanic/titanic_test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1e0932e8>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data=X_test_Out.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>1044</td>\n",
       "      <td>3</td>\n",
       "      <td>Storey, Mr. Thomas</td>\n",
       "      <td>male</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3701</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Pclass                Name   Sex   Age  SibSp  Parch Ticket  \\\n",
       "152         1044       3  Storey, Mr. Thomas  male  60.5      0      0   3701   \n",
       "\n",
       "     Fare Cabin Embarked  \n",
       "152   NaN   NaN        S  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test_Out[(pd.isnull(X_test_Out.Fare))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1da42ba8>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=train, x='Pclass', y='Fare')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_test_Out[(pd.isnull(X_test_Out.Fare))].Fare = 10\n",
    "X_test_Out.loc[152,'Fare'] = 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>male</th>\n",
       "      <th>Q</th>\n",
       "      <th>S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892</td>\n",
       "      <td>3</td>\n",
       "      <td>34.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8292</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>893</td>\n",
       "      <td>3</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>894</td>\n",
       "      <td>2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6875</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>895</td>\n",
       "      <td>3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.6625</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>896</td>\n",
       "      <td>3</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12.2875</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Pclass   Age  SibSp  Parch     Fare  male  Q  S\n",
       "0          892       3  34.5      0      0   7.8292     1  1  0\n",
       "1          893       3  47.0      1      0   7.0000     0  0  1\n",
       "2          894       2  62.0      0      0   9.6875     1  1  0\n",
       "3          895       3  27.0      0      0   8.6625     1  0  1\n",
       "4          896       3  22.0      1      1  12.2875     0  0  1"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test_Out['Age'] = X_test_Out[['Age', 'Pclass']].apply(impute_age, axis=1) # replace blank age with pClass age mean\n",
    "\n",
    "X_test_Out.drop(labels='Cabin', axis=1, inplace=True) # inplace modifies same dataset no need to assign output\n",
    "\n",
    "sex_o = pd.get_dummies(X_test_Out['Sex'], drop_first=True)\n",
    "embark_o = pd.get_dummies(X_test_Out['Embarked'], drop_first=True)\n",
    "\n",
    "X_test_Out.drop(labels=['Sex','Embarked', 'Name', 'Ticket'], axis=1, inplace = True)\n",
    "\n",
    "X_test_Out = pd.concat([X_test_Out,sex_o,embark_o], axis=1)\n",
    "\n",
    "X_test_Out.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1e1c7470>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data=X_test_Out.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0,\n",
       "       1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1,\n",
       "       1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1,\n",
       "       1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1,\n",
       "       1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,\n",
       "       0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0,\n",
       "       1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1,\n",
       "       0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1,\n",
       "       1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,\n",
       "       0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0,\n",
       "       1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n",
       "       0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1,\n",
       "       0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0,\n",
       "       0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0,\n",
       "       0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,\n",
       "       1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0,\n",
       "       0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0,\n",
       "       1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1,\n",
       "       0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions_Out = logmodel.predict(X_test_Out)\n",
    "predictions_Out\n",
    "#pd.to_csv(predictions_Out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Survived\n",
       "0         0\n",
       "1         0\n",
       "2         0\n",
       "3         0\n",
       "4         1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#import numpy\n",
    "output = pd.DataFrame(predictions_Out, columns=['Survived'])\n",
    "output.head()\n",
    "#numpy.stack([pds[pds.index[i]] for i in range(118)], axis=0)\n",
    "#output = pd.concat([X_test_Out.PassengerId,output], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#header = [\"PassengerId\", \"Survived\"]\n",
    "#output.to_csv('titanic_generated_submission.csv', columns = header)\n",
    "output = pd.concat([X_test_Out.PassengerId,output], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived\n",
       "PassengerId          \n",
       "892                 0\n",
       "893                 0\n",
       "894                 0\n",
       "895                 0\n",
       "896                 1"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output.set_index('PassengerId', inplace=True)\n",
    "output.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "output.to_csv('dataset/kaggle-titanic/titanic_generated_submission.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kaggle Score - 74.641%"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}